AI systems are no longer theoretical targets — they’re already being exploited. From jailbreaks and prompt injections to data leaks and agent manipulation, attackers are using simple language to probe and break systems once thought secure. Traditional pentesting can’t keep pace with this reality. AI behaves unpredictably, its vulnerabilities change with context and every new update or integration introduces fresh risk.
In this session, we’ll explore why AI needs an entirely new red teaming playbook. You’ll hear real-world evidence of how even the most advanced models fail under adversarial testing, and why continuous red teaming — across models, applications and agents — is now essential. We’ll break down how red teaming works in practice, from simulating guardrail bypasses and data exfiltration to uncovering context-driven flaws that only appear in deployment.
You’ll learn:
- Why AI’s nondeterministic nature breaks the old red-teaming model.
- The most common attack vectors enterprises face today.
- How vulnerabilities differ in models, applications and agents.
- How continuous red teaming builds confidence for developers, executives and customers alike.
Join us to see how AI red teaming turns hidden flaws into actionable insights — helping you protect your business before attackers exploit the gaps.
